FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3148643908> ?p ?o ?g. }

• W3148643908 endingPage "3105" @default.
• W3148643908 startingPage "3099" @default.
• W3148643908 abstract "Early cancer detection is significant for patient mortality rate reduction. Although machine learning has been widely employed in that context, there are still deficiencies. In this work, we studied different machine learning algorithms for early cancer detection and proposed an Adaptive Support Vector Machine (ASVM) method by synergizing Shuffled Frog Leaping Algorithm and Support Vector Machine (SVM) in this study.Since ASVM regulates SVM for parameter adaption based on data characteristics, the experimental results reflected the robust generalization capability of ASVM on different datasets under different settings; for instance, ASVM can enhance the sensitivity by over 10% for early cancer detection compared with SVM. Besides, our proposed ASVM outperformed Grid Search + SVM and Random Search + SVM by significant margins in terms of the area under the ROC curve (AUC) (0.938 versus 0.922 versus 0.921).The proposed algorithm and dataset are available at https://github.com/ElaineLIU-920/ASVM-for-Early-Cancer-Detection.Supplementary data are available at Bioinformatics online." @default.
• W3148643908 created "2021-04-13" @default.
• W3148643908 creator A5023836500 @default.
• W3148643908 creator A5030015771 @default.
• W3148643908 creator A5032961872 @default.
• W3148643908 date "2021-04-09" @default.
• W3148643908 modified "2023-10-15" @default.
• W3148643908 title "Early cancer detection from genome-wide cell-free DNA fragmentation via shuffled frog leaping algorithm and support vector machine" @default.
• W3148643908 cites W1533135466 @default.
• W3148643908 cites W1965151932 @default.
• W3148643908 cites W1972978214 @default.
• W3148643908 cites W2015438948 @default.
• W3148643908 cites W2021100122 @default.
• W3148643908 cites W2027735722 @default.
• W3148643908 cites W2038411763 @default.
• W3148643908 cites W2040294496 @default.
• W3148643908 cites W2050126859 @default.
• W3148643908 cites W2052352830 @default.
• W3148643908 cites W2056137745 @default.
• W3148643908 cites W2056716237 @default.
• W3148643908 cites W2070493638 @default.
• W3148643908 cites W2088512088 @default.
• W3148643908 cites W2095234124 @default.
• W3148643908 cites W2106905228 @default.
• W3148643908 cites W2108728387 @default.
• W3148643908 cites W2117906597 @default.
• W3148643908 cites W2122111042 @default.
• W3148643908 cites W2124044364 @default.
• W3148643908 cites W2131822674 @default.
• W3148643908 cites W2169977526 @default.
• W3148643908 cites W2170379523 @default.
• W3148643908 cites W2239118478 @default.
• W3148643908 cites W2312404985 @default.
• W3148643908 cites W2339885376 @default.
• W3148643908 cites W2464284977 @default.
• W3148643908 cites W2479773785 @default.
• W3148643908 cites W2563823863 @default.
• W3148643908 cites W2737607818 @default.
• W3148643908 cites W2760946358 @default.
• W3148643908 cites W2792617097 @default.
• W3148643908 cites W2899311685 @default.
• W3148643908 cites W2911964244 @default.
• W3148643908 cites W2947989913 @default.
• W3148643908 cites W3045004532 @default.
• W3148643908 cites W4248220371 @default.
• W3148643908 cites W4252684946 @default.
• W3148643908 doi "https://doi.org/10.1093/bioinformatics/btab236" @default.
• W3148643908 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33837381" @default.
• W3148643908 hasPublicationYear "2021" @default.
• W3148643908 type Work @default.
• W3148643908 sameAs 3148643908 @default.
• W3148643908 citedByCount "9" @default.
• W3148643908 countsByYear W31486439082021 @default.
• W3148643908 countsByYear W31486439082022 @default.
• W3148643908 countsByYear W31486439082023 @default.
• W3148643908 crossrefType "journal-article" @default.
• W3148643908 hasAuthorship W3148643908A5023836500 @default.
• W3148643908 hasAuthorship W3148643908A5030015771 @default.
• W3148643908 hasAuthorship W3148643908A5032961872 @default.
• W3148643908 hasConcept C11413529 @default.
• W3148643908 hasConcept C119857082 @default.
• W3148643908 hasConcept C12267149 @default.
• W3148643908 hasConcept C134306372 @default.
• W3148643908 hasConcept C151730666 @default.
• W3148643908 hasConcept C153180895 @default.
• W3148643908 hasConcept C154945302 @default.
• W3148643908 hasConcept C177148314 @default.
• W3148643908 hasConcept C2779343474 @default.
• W3148643908 hasConcept C33923547 @default.
• W3148643908 hasConcept C41008148 @default.
• W3148643908 hasConcept C86803240 @default.
• W3148643908 hasConcept C95922358 @default.
• W3148643908 hasConceptScore W3148643908C11413529 @default.
• W3148643908 hasConceptScore W3148643908C119857082 @default.
• W3148643908 hasConceptScore W3148643908C12267149 @default.
• W3148643908 hasConceptScore W3148643908C134306372 @default.
• W3148643908 hasConceptScore W3148643908C151730666 @default.
• W3148643908 hasConceptScore W3148643908C153180895 @default.
• W3148643908 hasConceptScore W3148643908C154945302 @default.
• W3148643908 hasConceptScore W3148643908C177148314 @default.
• W3148643908 hasConceptScore W3148643908C2779343474 @default.
• W3148643908 hasConceptScore W3148643908C33923547 @default.
• W3148643908 hasConceptScore W3148643908C41008148 @default.
• W3148643908 hasConceptScore W3148643908C86803240 @default.
• W3148643908 hasConceptScore W3148643908C95922358 @default.
• W3148643908 hasFunder F4320309893 @default.
• W3148643908 hasFunder F4320321001 @default.
• W3148643908 hasFunder F4320323291 @default.
• W3148643908 hasFunder F4320334123 @default.
• W3148643908 hasFunder F4320335055 @default.
• W3148643908 hasIssue "19" @default.
• W3148643908 hasLocation W31486439081 @default.
• W3148643908 hasLocation W31486439082 @default.
• W3148643908 hasOpenAccess W3148643908 @default.
• W3148643908 hasPrimaryLocation W31486439081 @default.
• W3148643908 hasRelatedWork W2041399278 @default.
• W3148643908 hasRelatedWork W2056016498 @default.
• W3148643908 hasRelatedWork W2136184105 @default.

• next